In all of these cases, personal data is accumulated — and manipulated — without individuals’ expressed consent. And while some may argue that using these applications implies consent, others counter that society has reached a critical juncture, and we must consider the moral and ethical questions generated by the growth of technologies such as artificial intelligence, machine learning and Big Data.

Ethics and computer science aren’t natural bedfellows. One of the earliest computer programmers, Grace Hopper, has been quoted as saying, “It’s easier to ask forgiveness than it is to get permission.” That’s pretty much been the modus operandi for computing products ever since: Build it first, then fix it if there are problems.

But the stakes have shifted now that certain technologies have life-changing consequences. Consider a machine-learning application that decides who gets reduced-cost housing or who is eligible for a medical procedure. Consider whether self-driving cars, controlled by AI, are safe enough to be on public roads.

Universities all over the country, from UCLA to MIT, are stepping up to train future engineers, data scientists, business executives and policymakers in the ethics of computer science.

Whether they are developing courses, hosting conferences or infusing ethics into everyday coursework, here are four ways university professionals are getting students to think differently about the ramifications of AI and Big Data:

1. Focus on Real-World Applications of Emerging Tech

Questionable ethics practices related to AI and to data usage and privacy are already popping up in corporations, as well as in governmental and other entities. At the University of Texas-Austin, the course “Ethical Foundations of Computer Science” asks students to discuss case studies to consider the impact of technology on society.

Stanford is developing a course using input from the disciplines of philosophy and political science. The goal is to have students consider topics from varied perspectives, such as those of a software engineer, a business strategist or a policymaker.

4. Develop Systematic Methods to Analyze Societal Issues

In Cornell’s data science course, students tackle real-world ethical challenges, such as how to handle a biased data set. In a New York Times article, Solon Barocas, an assistant professor, said the course “was really focused on trying to help them understand what in their everyday practice as a data scientist they are likely to confront, and to help them think through these challenges more systematically.”